As a distinctive resource of Chinese civilization， traditional Chinese medicine （TCM） technology transfer faces significant opportunities under the background of digital and intelligent transformation， while also being constrained by unique challenges such as the complexity of its theoretical system， lengthy industrial chains， and multidimensional policy restrictions， resulting in a "high-value-high-threshold" paradox. At present， TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma， i.e.， unwillingness to transfer， inability to transfer， and lack of capacity to transfer. Specifically， the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements， unclear ownership and compliance risks suppress innovation incentives， and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems， blockchain-based traceability， and AI diagnostic models， the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization， promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example， a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements， while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization， reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead， through the construction of national-level databases， the cultivation of interdisciplinary talent， and the mutual recognition of international standards， a new paradigm of "scientific intelligent manufacturing" can be formed， providing systematic solutions for the modernization of TCM and global health governance.

ObjectiveTraditional Chinese medicine (TCM) constitutes a valuable cultural heritage and an important source of antitumor compounds. Poria (Poria cocos (Schw.) Wolf), the dried sclerotium of a polyporaceae fungus, was first documented in Shennong’s Classic of Materia Medica and has been used therapeutically and dietarily in China for millennia. Traditionally recognized for its diuretic, spleen-tonifying, and sedative properties, modern pharmacological studies confirm that Poria exhibits antioxidant, anti-inflammatory, antibacterial, and antitumor activities. Pachymic acid (PA; a triterpenoid with the chemical structure 3β-acetyloxy-16α-hydroxy-lanosta-8,24(31)-dien-21-oic acid), isolated from Poria, is a principal bioactive constituent. Emerging evidence indicates PA exerts antitumor effects through multiple mechanisms, though these remain incompletely characterized. Neuroblastoma (NB), a highly malignant pediatric extracranial solid tumor accounting for 15% of childhood cancer deaths, urgently requires safer therapeutics due to the limitations of current treatments. Although PA shows multi-mechanistic antitumor potential, its efficacy against NB remains uncharacterized. This study systematically investigated the potential molecular targets and mechanisms underlying the anti-NB effects of PA by integrating network pharmacology-based target prediction with experimental validation of multi-target interactions through molecular docking, dynamic simulations, and in vitro assays, aimed to establish a novel perspective on PA’s antitumor activity and explore its potential clinical implications for NB treatment by integrating computational predictions with biological assays. MethodsThis study employed network pharmacology to identify potential targets of PA in NB, followed by validation using molecular docking, molecular dynamics (MD) simulations, MM/PBSA free energy analysis, RT-qPCR and Western blot experiments. Network pharmacology analysis included target screening via TCMSP, GeneCards, DisGeNET, SwissTargetPrediction, SuperPred, and PharmMapper. Subsequently, potential targets were predicted by intersecting the results from these databases via Venn analysis. Following target prediction, topological analysis was performed to identify key targets using Cytoscape software. Molecular docking was conducted using AutoDock Vina, with the binding pocket defined based on crystal structures. MD simulations were performed for 100 ns using GROMACS, and RMSD, RMSF, SASA, and hydrogen bonding dynamics were analyzed. MM/PBSA calculations were carried out to estimate the binding free energy of each protein-ligand complex. In vitro validation included RT-qPCR and Western blot, with GAPDH used as an internal control. ResultsThe CCK-8 assay demonstrated a concentration-dependent inhibitory effect of PA on NB cell viability. GO analysis suggested that the anti-NB activity of PA might involve cellular response to chemical stress, vesicle lumen, and protein tyrosine kinase activity. KEGG pathway enrichment analysis suggested that the anti-NB activity of PA might involve the PI3K/AKT, MAPK, and Ras signaling pathways. Molecular docking and MD simulations revealed stable binding interactions between PA and the core target proteins AKT1, EGFR, SRC, and HSP90AA1. RT-qPCR and Western blot analyses further confirmed that PA treatment significantly decreased the mRNA and protein expression of AKT1, EGFR, and SRC while increasing the HSP90AA1 mRNA and protein levels. ConclusionIt was suggested that PA may exert its anti-NB effects by inhibiting AKT1, EGFR, and SRC expression, potentially modulating the PI3K/AKT signaling pathway. These findings provide crucial evidence supporting PA’s development as a therapeutic candidate for NB.

This study aimed to investigate the effect of Dahuang Zhechong Pills(DHZCP) in delaying heart aging(HA) and explore the potential mechanism. Network pharmacology and molecular docking were employed to explore the targets and potential mechanisms of DHZCP in delaying HA. Furthermore, in vitro experiments were conducted with the DHZCP-containing serum to verify key targets and pathways in D-galactose(D-gal)-induced aging of cardiomyocytes. Active components of DHZCP were searched against the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform(TCSMP), and relevant targets were predicted. HA-related targets were screened from the GeneCards, Online Mendelian Inheritance in Man(OMIM), and DisGeNET. The common targets shared by the active components of DHZCP and HA were used to construct a protein-protein interaction network in STRING 12.0, and core targets were screened based on degree in Cytoscape 3.9.1. Metaspace was used for Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) enrichment analyses of the core targets to predict the mechanisms. Molecular docking was performed in AutoDock Vina. The results indicated that a total of 774 targets of the active components of DHZCP and 4 520 targets related to HA were screened out, including 510 common targets. Core targets included B-cell lymphoma 2(BCL-2), serine/threonine kinase 1(AKT1), and hypoxia-inducible factor 1 subunit A(HIF1A). The GO and KEGG enrichment analyses suggested that DHZCP mainly exerted its effects via the phosphatidylinositol 3-kinase(PI3K)/AKT signaling pathway, HIF-1α signaling pathway, longevity signaling pathway, and apoptosis signaling pathway. Among the pathways predicted by GO and KEGG enrichment analyses, the PI3K/AKT/HIF-1α signaling pathway was selected for verification. The cell-counting kit 8(CCK-8) assay showed that D-gal significantly inhibited the proliferation of H9c2 cells, while DHZCP-containing serum increased the viability of H9c2 cells. SA-β-gal staining revealed a significant increase in the number of blue-green positive cells in the D-gal group, which was reduced by DHZCP-containing serum. TUNEL staining showed that DHZCP-containing serum decreased the number of apoptotic cells. After treatment with DHZCP-containing serum, the protein levels of Klotho, BCL-2, p-PI3K/PI3K, p-AKT1/AKT1, and HIF-1α were up-regulated, while those of P21, P16, BCL-2 associated X protein(Bax), and cleaved caspase-3 were down-regulated. The results indicated that DHZCP delayed HA via multiple components, targets, and pathways. Specifically, DHZCP may delay HA by reducing apoptosis via activating the PI3K/AKT/HIF-1α signaling pathway.
Proto-Oncogene Proteins c-akt/genetics* ; Drugs, Chinese Herbal/pharmacology* ; Signal Transduction/drug effects* ; Apoptosis/drug effects* ; Myocytes, Cardiac/cytology* ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Phosphatidylinositol 3-Kinases/genetics* ; Animals ; Rats ; Humans ; Molecular Docking Simulation ; Aging/metabolism* ; Protein Interaction Maps/drug effects* ; Heart/drug effects* ; Network Pharmacology

This study explores the role and underlying molecular mechanisms of fucoidan sulfate(FPS) in regulating heme oxygenase-1(Hmox1)-mediated ferroptosis to ameliorate myocardial injury in diabetic cardiomyopathy(DCM) through in vivo and in vitro experiments and network pharmacology analysis. In vivo, a DCM rat model was established using a combination of "high-fat diet feeding + two low-dose streptozotocin(STZ) intraperitoneal injections". The rats were randomly divided into four groups: normal, model, FPS, and dapagliflozin(Dapa) groups. In vitro, a cellular model was created by inducing rat cardiomyocytes(H9c2 cells) with high glucose(HG), using zinc protoporphyrin(ZnPP), an Hmox1 inhibitor, as the positive control. An automatic biochemical analyzer was used to measure blood glucose(BG), serum aspartate aminotransferase(AST), serum lactate dehydrogenase(LDH), and serum creatine kinase-MB(CK-MB) levels. Echocardiography was used to assess rat cardiac function, including ejection fraction(EF) and fractional shortening(FS). Pathological staining was performed to observe myocardial morphology and fibrotic characteristics. DCFH-DA fluorescence probe was used to detect reactive oxygen species(ROS) levels in myocardial tissue. Specific assay kits were used to measure serum brain natriuretic peptide(BNP), myocardial Fe~(2+), and malondialdehyde(MDA) levels. Western blot(WB) was used to detect the expression levels of myosin heavy chain 7B(MYH7B), natriuretic peptide A(NPPA), collagens type Ⅰ(Col-Ⅰ), α-smooth muscle actin(α-SMA), ferritin heavy chain 1(FTH1), solute carrier family 7 member 11(SLC7A11), glutathione peroxidase 4(GPX4), 4-hydroxy-2-nonenal(4-HNE), and Hmox1. Immunohistochemistry(IHC) was used to examine Hmox1 protein expression patterns. FerroOrange and Highly Sensitive DCFH-DA fluorescence probes were used to detect intracellular Fe~(2+) and ROS levels. Transmission electron microscopy was used to observe changes in mitochondrial morphology. In network pharmacology, FPS targets were identified through the PubChem database and PharmMapper platform. DCM-related targets were integrated from OMIM, GeneCards, and DisGeNET databases, while ferroptosis-related targets were obtained from the FerrDb database. A protein-protein interaction(PPI) network was constructed for the intersection of these targets using STRING 11.0, and core targets were screened with Cytoscape 3.9.0. Molecular docking analysis was conducted using AutoDock and PyMOL 2.5. In vivo results showed that FPS significantly reduced AST, LDH, CK-MB, and BNP levels in DCM model rats, improved cardiac function, decreased the expression of myocardial injury proteins(MYH7B, NPPA, Col-Ⅰ, and α-SMA), alleviated myocardial hypertrophy and fibrosis, and reduced Fe~(2+), ROS, and MDA levels in myocardial tissue. Furthermore, FPS regulated the expression of ferroptosis-related markers(Hmox1, FTH1, SLC7A11, GPX4, and 4-HNE) to varying degrees. Network pharmacology results revealed 313 potential targets for FPS, 1 125 targets for DCM, and 14 common targets among FPS, DCM, and FerrDb. Hmox1 was identified as a key target, with FPS showing high docking activity with Hmox1. In vitro results demonstrated that FPS restored the expression levels of ferroptosis-related proteins, reduced intracellular Fe~(2+) and ROS levels, and alleviated mitochondrial structural damage in cardiomyocytes. In conclusion, FPS improves myocardial injury in DCM, with its underlying mechanism potentially involving the regulation of Hmox1 to inhibit ferroptosis. This study provides pharmacological evidence supporting the therapeutic potential of FPS for DCM-induced myocardial injury.
Animals ; Ferroptosis/drug effects* ; Rats ; Diabetic Cardiomyopathies/physiopathology* ; Male ; Rats, Sprague-Dawley ; Polysaccharides/pharmacology* ; Heme Oxygenase-1/genetics* ; Myocytes, Cardiac/metabolism* ; Myocardium/pathology* ; Humans ; Cell Line ; Heme Oxygenase (Decyclizing)

In this study,a sensitive lateral flow immunoassay(LFIA)platform based on carbon dots-mesoporous silica nanocomposite(CD-MSNs)fluorescent probes was constructed for high-performance detection of inflammatory marker interleukin-6(IL-6).Green fluorescent carbon dots(CDs)were prepared by hydrothermal method with 3,9-perylenic acid and 3-aminopropyltriethoxysilane(APTES)as raw materials,and highly fluorescent CD-MSNs composites were then constructed by encapsulating the prepared CDs in mesoporous silica nanoparticles(MSNs).Fluorescent probes were prepared by covalent coupling of CD-MSNs with IL-6 antibody.Fluorescent immunochromatographic test strips were constructed by spraying IL-6 capture antibody and goat anti-mouse IgG on nitrocellulose membrane as detection line(T-line)and quality control line(C-line),respectively.The fluorescence immunoassay analyzer was used to quantitatively detect the fluorescence intensity of T-line,and the experimental results showed that the LFIA platform based on this probe had a good linear relationship in IL-6 concentration range of 102-106 pg/mL,and the detection limit was 64 pg/mL,which was two orders of magnitude more sensitive than that of the traditional colloidal gold test strips.This method effectively solved the issue of insufficient sensitivity of traditional LFIA technique,and provided a rapid and highly sensitive detection method for early diagnosis of inflammatory diseases.

Objective To investigate different doses of the analgesic effects of dezocine comparing with sufentanil after laryngectomy.Methods A total of 129 patients who underwent elective partial laryngectomy from Feb 2022 to Jan 2023 were randomly assigned to dezocine 0.5 mg/kg group(group D1),dezocine 0.6 mg/kg group(group D2)and sufentanil 2 μg/kg group(group S).Twenty-four hours amount of drugs,the visual analogue scale(visual analogue scale,VAS)and 48 h total pressing times of PCA(patient-controlled intravenous analgesia,PCIA)were compared among the three groups at 6,12,24 and 48 h after operation,and the postoperative adverse reactions(nausea,vomiting,dizziness,urinary retention and respiratory depression)were recorded.Results There was no significant difference in 24 h amount of drugs among the three groups.The VAS score of group D1 was higher than that of group S at 6 h postoperatively(P＜0.05),but did not differ significantly among the three groups at 12,24 and 48 h.There was no significant differences in the number of compressions and postoperative adverse reactions among the three groups.Conclusion Compared with sufentanil,0.6 mg/kg dezocine can provide the same degree of analgesic effect.However,no advantage was found to reduce adverse reactions.

With the increasing application of immune checkpoint inhibitors(ICI)in anti-tumor therapy,ICI related infections are often neglected.Mycobacterium tuberculosis(MTB)is also a common pathogen.We reported a case of ICI related pulmonary tuberculosis from Zhongshan Hospital,Fudan University.Meanwhile,18 cases of ICI related tuberculosis infection were collected through literature search,and the characteristics of ICI related tuberculosis were analyzed to improve the understanding in clinic practice.All the cases were confirmed TB including 15 cases of pulmonary tuberculosis(1 case with complication of intestinal tuberculosis)and 4 cases of extra-pulmonary tuberculosis(1 case of disseminated tuberculosis,bone tuberculosis,tuberculous pericarditis and tuberculous pleurisy,respectively).The chest CT characteristics of pulmonary tuberculosis mainly included centrilobular nodules,ground glass nodules,empty lesions,patchy shadows,consolidation and large infiltration.Eighteen cases started anti-tuberculosis treatment,while 4 cases continued ICI treatment.Three cases suspended ICI(2 cases had remission after reuse)and 11 cases stopped ICI,and 1 case was not mentioned.ICI related tuberculosis may be a direct complication of tumor immunotherapy.It is necessary to screen tuberculosis infection and exclude active tuberculosis before immunotherapy.If there are suspected symptoms such as fever,cough and sputum during ICI treatment,active tuberculosis should be taken into account.

ObjectiveTo investigate the genetic polymorphism and structure of 47 autosomal microhaplotypes in the Han population in Changshu City, Jiangsu Province, and to evaluate the forensic efficiencies and forensic parameters. MethodsThe DNA library of unrelated individual samples was prepared according to MHSeqTyper47 kit manual and sequenced on the MiSeq FGx platform. Microhaplotype genotyping and sequencing depth statistics were processed using MHTyper. The genetic information of samples was then evaluated. The fixation index and genetic distance between the Jiangsu Changshu population and the reference populations in the 1000 Genomes Project phase 3 (1KG) were calculated, and forensic parameters were evaluated. ResultsThe fixation index and genetic distance between the Han population in Changshu, Jiangsu, and the CHB (Han Chinese in Beijing, China) reference population in 1KG were the lowest. The effective allele number (A_e) of each locus is also the closest between the two populations. The combined matching probability (CMP) of the Changshu Han population is close to the 5 populations of the East Asian reference super-population in 1KG, which is 1.25×10^-36, and the combined probability of exclusion reached 0.999 999 999 964 1. ConclusionThis study reported the genetic polymorphism and allele frequency of 47 microhaplotypes in a Han population in Changshu City, Jiangsu Province. This information provides a data basis for 47 microhaplotypes in forensic applications. In addition, the polymorphism differences between the 1KG reference population and the Han population in Changshu, Jiangsu were compared, and the genetic structure of 47 microhaplotypes in the Han population in Changshu, Jiangsu was revealed. In general, the reference data of the East Asian super-population in 1KG is more in line with the genetic characteristics of Han population in Changshu, Jiangsu.

OBJECTIVE To establish a performance index evaluation system for pharmacists in inpatient pharmacy to encourage and guide pharmacists to achieve self-professional growth and reshape their own values. METHODS According to the evaluation criteria for the construction of provincial-level clinical specialties in Jiangsu province, the key success factors(KSF) method was used to set the key indicators for the discipline construction of the department, and the key process indicator(KPI) method was used for the daily work of the department. Based on the combination of KSF and KPI, an inpatient pharmacy performance management system was established, employee and clinical satisfaction, ward complaints, error occurrence rate, dispensing efficiency, and scientific research output were taken as indicators to evaluate the effect after the implementation of the performance management system. RESULTS Before and after the construction and implementation of the "KSF + KPI" performance system, the average employee satisfaction had increased from 57.75% to 77.81%(P<0.05), the number of complaints in the ward had decreased from (26.33±6.75) per month to (7.17±3.61) per month, and the number of errors had decreased from (30.33±5.50) per month to (12.58±2.75) per month, the differences were statistically significant(P<0.05). Overall clinical satisfaction reached 81.13%; the PIVAS blending efficiency had been improved to a certain extent, with an average increase of 17%. Innovation related indicators such as article writing, recruitment, project application, and employee research participation had significantly improved after implementation of the indicator performance system. CONCLUSION The inpatient pharmacy performance management system establishes based on "KSF and KPI" provides a good performance evaluation scheme for the transformation and development of the dispensing department of the pharmaceutical department. It has made positive exploration in the aspects of self-motivation and professional development of hospital pharmacists, high-efficiency operation, improvement of clinical service level and development of pharmaceutical discipline, and has achieved good results.

Near infrared spectroscopy(NIRS)technology combined with chemometrics algorithms has been widely used in quantitative and qualitative analysis of food and medicine.However,traditional chemometrics methods,especially linear classification methods,often yield unsatisfactory results when addressing multi-class classification problems.Convolutional neural network(CNN)is adept at extracting deep-level features from data and suitable for handling non-linear relationships.The modeling performance of CNN depends on the size and diversity of sample,while the collection and preprocessing of NIRS sample data is often time-consuming and labor-intensive.This study proposed a NIRS qualitative analysis method based on data augmentation strategies and CNN.The data augmentation strategy included two steps.Firstly,applying Bootstrap resampling and generative adversarial network(GAN)methods to augment three NIRS datasets(Medicine,coffee and grape).Secondly,combining the original samples(Y)with the Bootstrap augmented samples(B)and GAN augmented samples(G)to obtain three augmented datasets(Y-B,Y-G and Y-B-G).Based on this,a CNN model structure suitable for these datasets was designed,consisting of 2 one-dimensional convolutional layers,1 max-pooling layer,and 1 fully connected layer.The results showed that compared to the optimal models of partial least squares discriminant analysis(PLS-DA),support vector machine(SVM),and back propagation neural network(BP),the CNN model based on Y-B dataset achieved average accuracy improvements of 3.998%,9.364%,and 4.689%for medicine(Binary classification);the CNN model based on the Y-B-G dataset achieved average accuracy improvements of 6.001%,2.004%,and 7.523%for coffee(7-class classification);and the CNN model based on the Y-B dataset achieved average accuracy improvements of 33.408%,51.994%,and 34.378%for grapes(20-class classification).It was evident that the models established based on data augmentation strategies and CNN demonstrated better classification accuracy and generalization performance with different datasets and classification categories.